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Towards a Practical Deployment of Privacy-preserving Crowd-sensing Tasks

Nicolas Haderer 1, 2, 3 Vincent Primault 4 Patrice Raveneau 5 Christophe Ribeiro 1, 2, 3 Romain Rouvoy 1, 2, 3 Sonia Ben Mokhtar 4
3 ADAM - Adaptive Distributed Applications and Middleware
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe
4 DRIM - Distribution, Recherche d'Information et Mobilité
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
5 URBANET - Réseaux capillaires urbains
CITI - CITI Centre of Innovation in Telecommunications and Integration of services, Inria Grenoble - Rhône-Alpes
Abstract : Recent generations of mobile phones, embedding a wide variety of sensors, have fostered the development of open sensing applications, such as network quality or weather forecast applications. In this paper, we present a novel privacy-preserving crowdsourcing platform relying on two components: APISENSE and PRIVAPI. APISENSE is a distributed middleware platform that leverages the dynamic deployment of crowdsourcing tasks across a population of mobile phones. PRIVAPI is a middleware handling privacy-preserving publication of mobility data.
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Contributor : Patrice Raveneau <>
Submitted on : Thursday, December 18, 2014 - 4:07:07 PM
Last modification on : Tuesday, June 1, 2021 - 2:08:07 PM
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Nicolas Haderer, Vincent Primault, Patrice Raveneau, Christophe Ribeiro, Romain Rouvoy, et al.. Towards a Practical Deployment of Privacy-preserving Crowd-sensing Tasks. Middleware Posters and Demos '14, Dec 2014, Bordeaux, France. ⟨10.1145/2678508.2678530⟩. ⟨hal-01095787⟩



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